This disclosure relates generally to the field of image processing, and more particularly to a system and a method for selecting a subset of hyperspectral imaging scene spectral covariance principal components to detect a material or target in a scene.
In many conventional image processing scenarios comprising hyperspectral imaging (HSI) systems, hyperspectral sensors collect data of an image from one spatial line and disperse the spectrum across a perpendicular direction of the focal plane of the optics receiving the image. Thus a focal plane pixel measures the intensity of a given spot on the ground in a specific waveband. A complete HSI cube scene is formed by scanning this spatial line across the scene that is imaged. The complete HSI cube may be analyzed as a measurement of the spectrum, the intensity in many wavebands, for a spatial pixel. This spatial pixel represents a given spot on the ground in a cross-scan direction for one of the lines at a given time in the scan direction. These spectra are analyzed to detect targets or spectral anomalies.